---
library_name: transformers
license: mit
base_model: indobenchmark/indobert-large-p2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# results

This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.8
- F1 Weighted: 0.7852
- Loss: 0.7316

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2.7820079535067715e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 17
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | F1 Weighted | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:-----------:|:---------------:|
| No log        | 1.0   | 6    | 0.24     | 0.1029      | 1.2189          |
| 1.2118        | 2.0   | 12   | 0.32     | 0.2521      | 1.1035          |
| 1.2118        | 3.0   | 18   | 0.64     | 0.5214      | 1.0049          |
| 1.0516        | 4.0   | 24   | 0.68     | 0.6394      | 0.8500          |
| 1.0014        | 5.0   | 30   | 0.64     | 0.628       | 0.8799          |
| 1.0014        | 6.0   | 36   | 0.68     | 0.6835      | 0.7949          |
| 1.1235        | 7.0   | 42   | 0.72     | 0.6931      | 0.8320          |
| 1.1235        | 8.0   | 48   | 0.64     | 0.6368      | 0.7677          |
| 1.0837        | 9.0   | 54   | 0.8      | 0.7852      | 0.7316          |
| 0.9824        | 10.0  | 60   | 0.76     | 0.7324      | 0.7318          |
| 0.9824        | 11.0  | 66   | 0.72     | 0.6966      | 0.7191          |
| 0.8334        | 12.0  | 72   | 0.76     | 0.7346      | 0.7128          |
| 0.8334        | 13.0  | 78   | 0.68     | 0.6430      | 0.7165          |
| 0.7175        | 14.0  | 84   | 0.68     | 0.6430      | 0.7259          |
| 0.6813        | 15.0  | 90   | 0.68     | 0.6430      | 0.7139          |
| 0.6813        | 16.0  | 96   | 0.72     | 0.6981      | 0.6977          |
| 0.6765        | 17.0  | 102  | 0.72     | 0.6981      | 0.6941          |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1